METHODS AND SYSTEMS FOR EXPLAINING A DECISION PROCESS OF A MACHINE LEARNING MODEL

A method and system for explaining a decision process of a machine learning model that includes inputting into a machine learning model a first input data file; receiving a first output data file from the machine learning model based on the first input data file; executing an adversarial attack on the machine learning model, creating a mapping of the one or more units of data of the first input data file with changes by the adversarial attack exceeding a first threshold to one or more segments of the first input data file; determining a density of the changes to the one or more units of data in each of the one or more segments; and displaying the one or more segments of the first input data file having a density of changes to the one or more units of data exceeding a second threshold via a graphical user interface.